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Multi-scale spatio-temporal transformer: A novel model reduction approach for day-ahead security-constrained unit commitment

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APPLIED ENERGY 2025年 380卷

作者： Liu, Mao Kong, Xiangyu Xiong, Kaizhi Wang, Jimin Lin, Qingxiang Tianjin Univ Key Lab Smart Grid Minist Educ Tianjin 300072 Peoples R China Yalong River Hydropower Dev Co Ltd Chengdu 610066 Peoples R China

security-constrained unit commitment (SCUC) in large-scale power systems faces significant computational challenges, particularly with increasing renewable energy integration. This paper introduces a multi-scale spatiotemporal transformer (MSTT) model for efficient SCUC problem reduction through three key innovations: a multi-scale ST attention mechanism integrating both hierarchical temporal attention and electrical distancebased spatial attention to capture complex system dependencies, a physics-informed position encoding method incorporating power system domain knowledge including electrical distance, power flow sensitivity, and generator stability characteristics, and an adaptive reduction strategy with dynamic threshold adjustment mechanism that automatically balances computational efficiency and solution reliability based on system states and prediction confidence. Experimental results on IEEE test systems demonstrate that the MSTT model achieves up to 69.5 % computational time reduction while maintaining solution optimality (base-normalized cost (BNC) <= 0.05 %), significantly outperforming existing approaches.

关键词： security-constrained unit commitment Multi-scale spatio-temporal transformer Model reduction Deep learning

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Deep reinforcement learning explanation-assisted integer variable reduction method for security-constrained unit commitment

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2025年 144卷

作者： Dai, Yuchen Xu, Wei Yan, Minghui Xue, Feng Zhao, Jianfeng Southeast Univ Sch Elect Engn 2 Sipailou Nanjing 210096 Peoples R China State Grid NARI 19 Chengxin Ave Nanjing 211100 Peoples R China

The large-scale security-constrained unit commitment (SCUC) is pivotal for ensuring the secure and economical operation of modern power systems. Formulated as a mixed-integer nonlinear programming problem, mathematical model-based methods struggle to balance computation efficiency and solution accuracy. While artificial intelligence methods offer promising potential, they face several obstacles, including limited interpretability and generalizability constraints. In light of these challenges, this paper proposes an interpretation method for deep reinforcement learning models that is used to reduce integer variables for large-scale SCUC problem. This method employs a Gaussian Mixture Model to cluster the decision outcomes of the agents and utilizes an improved decision tree to interpret the clustering results. We analyze the physical implications behind the phenomenon of unit output distributions exhibiting multiple independent Gaussian distributions. Then, these interpretations are applied to identify active integer variables, thereby simplifying the complexity of the SCUC problem and enhancing solution efficiency. Furthermore, an improved Markov decision process model with domain knowledge pertinent of power systems is constructed to enhance the interpretability and reliability of the agents. A distinctive feature of this model is the incorporation of a bidirectional mapping of unsafe and safe actions. The case studies on the SG-126 system demonstrate that the proposed method achieves a significant increase in solution speed without loss of accuracy. The identified active integer variables are proven to be accurate and effective, contributing to improve computation efficiency of unit commitment. The proposed method also provides a novel explainable artificial intelligence-assisted method for complex decision-making problems in other fields.

关键词： security-constrained unit commitment Deep reinforcement learning Decision trees Explainable artificial intelligence

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security-constrained unit commitment With Linearized System Frequency Limit Constraints

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IEEE TRANSACTIONS ON POWER SYSTEMS 2014年第4期29卷 1536-1545页

作者： Ahmadi, Hamed Ghasemi, Hassan Univ British Columbia Sch Elect & Comp Engn Vancouver BC V6T 1Z4 Canada Univ Tehran Sch Elect & Comp Engn Tehran Iran

Rapidly increasing the penetration level of renewable energies has imposed new challenges to the operation of power systems. Inability or inadequacy of these resources in providing inertial and primary frequency responses is one of the important challenges. In this paper, this issue is addressed within the framework of security-constrained unit commitment (SCUC) by adding new constraints representing the system frequency response. A modified system frequency response model is first derived and used to find analytical representation of system minimum frequency in thermal-dominant multi-machine systems. Then, an effective piecewise linearization (PWL) technique is employed to linearize the nonlinear function representing the minimum system frequency, facilitating its integration in the SCUC problem. The problem is formulated as a mixed-integer linear programming (MILP) problem which is solved efficiently by available commercial solvers. The results indicate that the proposed method can be utilized to integrate renewable resources into power systems without violating system frequency limits.

关键词： Inertial response primary frequency control security-constrained unit commitment wind power

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security-constrained unit commitment for Electricity Market: Modeling, Solution Methods, and Future Challenges

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IEEE TRANSACTIONS ON POWER SYSTEMS 2023年第5期38卷 4668-4681页

作者： Chen, Yonghong Pan, Feng Qiu, Feng Xavier, Alinson S. Zheng, Tongxin Marwali, Muhammad Knueven, Bernard Guan, Yongpei Luh, Peter B. Wu, Lei Yan, Bing Bragin, Mikhail A. Zhong, Haiwang Giacomoni, Anthony Baldick, Ross Gisin, Boris Gu, Qun Philbrick, Russ Li, Fangxing Midcontinent Independent Syst Operator Inc Carmel IN 46032 USA Pacific Northwest Natl Lab Elect Infrastruct Richland WA 99532 USA Argonne Natl Lab Lemont IL 60439 USA ISO New England Holyoke MA 01040 USA NYISO Rensselaer NY 12144 USA Natl Renewable Energy Lab Computat Sci Ctr Golden CO 80401 USA Univ Florida Ind & Syst Engn Gainesville FL 32611 USA Univ Conneticut Comp Engn Storrs CT 06269 USA Stevens Inst Technol Hoboken NJ 07030 USA Rochester Inst Technol Elect & Microelect Engn Rochester NY 14623 USA Univ Connecticut Elect & Comp Engn Storrs CT 06269 USA Tsinghua Univ Elect Engn Beijing 100084 Peoples R China PJM Audubon PA 19403 USA Univ Texas Austin Elect & Comp Engn Austin TX 78712 USA PowerGEM LLC Co Clifton Pk NY 12065 USA Polaris Syst Optimizat Shoreline WA 98177 USA Univ Tennessee EECS Knoxville TN 37996 USA

This paper summarizes the technical activities of the IEEE Task Force on Solving Large Scale Optimization Problems in Electricity Market and Power System Applications. This Task Force was established by the IEEE Technology and Innovation Subcommittee to first review the state-of-the-art of the security-constrained unit commitment (SCUC) business model, its mathematical formulation, and solution techniques in solving electricity market clearing problems. The Task Force then investigated the emerging challenges of future market clearing problems and presented efforts in building benchmark mathematical and business models.

关键词： Combined cycle decomposition distributed energy resource electricity market mixed-integer programming network security analysis relaxation security-constrained unit commitment storage virtual transaction

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security-constrained unit commitment With AC/DC Transmission Systems

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IEEE TRANSACTIONS ON POWER SYSTEMS 2010年第1期25卷 531-542页

作者： Lotfjou, Azim Shahidehpour, Mohammad Fu, Yong Li, Zuyi IIT Dept Elect & Comp Engn Chicago IL 60616 USA

This paper presents the solution to the security-constrained unit commitment (SCUC) problem with a detailed representation of high voltage direct current (DC) transmission system with current source converters (CSCs). The SCUC problem is decomposed into a master problem for solving unit commitment (UC) problem and hourly transmission security check subproblems that evaluate branch flows and bus voltages of integrated AC/DC transmission systems. The solution of the transmission security check subproblem is based on a linear programming (LP) formulation that minimizes AC bus mismatches subject to AC/DC transmission constraints. The final SCUC solution prescribes an economic and secure operation and control strategy for AC/DC transmission systems and coordinates DC power transfers for enhancing the economics and the security of AC transmission systems. Numerical tests illustrate the efficiency of the proposed AC/DC transmission model.

关键词： AC/DC transmission systems Benders decomposition current source converters security-constrained unit commitment

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security-constrained unit commitment for AC-DC Grids With Generation and Load Uncertainty

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IEEE TRANSACTIONS ON POWER SYSTEMS 2018年第3期33卷 2717-2732页

作者： Bahrami, Shahab Wong, Vincent W. S. Univ British Columbia Dept Elect & Comp Engn Vancouver BC V6T 1Z4 Canada

The uncertainties in renewable generators and load demand make it a challenge for system operators to execute the security-constrained unit commitment (SCUC) program in an ac-dc grid. The SCUC is a nonlinear mixed-integer optimization problem due to the power flow equations, constraints imposed by the ac-dc converters, and the binary variables associated with the generators' on/off state. In this paper, we study the SCUC problem in ac-dc grids with generation and load uncertainty. We introduce the concept of conditional value-at-risk to limit the risk of deviations in the load demand and renewable generation. We relax the binary variables and introduce a l(1)-norm regularization term to the objective function, and then use convex relaxation techniques to transform the problem into a semidefinite program (SDP). We develop an algorithm based on the iterative reweighted l(1)-norm approximation that involves solving a sequence of SDPs. Simulations are performed on an IEEE 30-bus test system. Results show that the proposed algorithm returns a solution within 2% gap from the global optimal solution for the underlying test system. When compared with the multi-stage algorithm in the literature, our algorithm has a lower running time and returns a solution with a smaller gap from the global optimal solution.

关键词： Conditional value-at-risk l(1)-norm regularization security-constrained unit commitment semidefinite program

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security-constrained unit commitment with wind generation and compressed air energy storage

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IET GENERATION TRANSMISSION & DISTRIBUTION 2012年第2期6卷 167-175页

作者： Daneshi, H. Srivastava, A. K. So Calif Edison Co Rosemead CA 91770 USA Washington State Univ Pullman WA 99164 USA

Wind power is one of the fastest growing renewable sources of generation in the U. S. and many other countries. As wind-generated electricity continues to grow, electric utilities increasingly grapple with the challenges of connecting that power to the grid although maintaining system security. It is difficult to predict and control the output of wind generation because of wind intermittency and a reserve capacity is required to deal with inherent uncertainty. This study presents an approach for security-constrained unit commitment (SCUC) with integration of an energy storage system (ESS) and wind generation. Compressed air energy storage (CAES) is considered as an alternative solution to store energy. For economical operation and control purposes, utilities with CAES are interested in the availability and the dispatch of CAES on an hourly basis, given the specific characteristics of CAES. The main contribution of this study is the development of enhanced SCUC formulation and solution techniques with wind power, CAES and multiple constraints including fuel and emission limit. Proposed approach allows simultaneous optimisation of the energy and the ancillary services (AS). Case studies with eight-bus and 118-bus systems are presented to validate the proposed model. This study also contributes by conducting comprehensive studies to analyse the impact of CAES system on locational pricing, economics, peak-load shaving, transmission congestion management, wind curtailment and environmental perspective.

关键词： peak-load shaving power system security 118-bus system wind generation control system security maintenance emission limit security-constrained unit commitment Power system management, operation and economics power generation economics Power system protection wind-generated electricity ancillary service wind curtailment power generation scheduling wind power plants wind power SCUC formulation compressed air energy storage Wind power plants power generation dispatch environmental perspective renewable source Other energy storage transmission congestion management CAES system reserve capacity power generation protection

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security-constrained unit commitment with volatile wind power generation

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IEEE TRANSACTIONS ON POWER SYSTEMS 2008年第3期23卷 1319-1327页

作者： Wang, Jianhui Shahidehpour, Mohammad Li, Zuyi IIT Dept Elect & Comp Engn Chicago IL 60616 USA

This paper presents a security-constrained unit commitment (SCUC) algorithm which takes into account the intermittency and volatility of wind power generation. The UC problem is solved in the master problem with the forecasted intermittent wind power generation. Next, possible scenarios are simulated for representing the wind power volatility. The initial dispatch is checked in the subproblem and generation redispatch is considered for satisfying the hourly volatility of wind power in simulated scenarios. If the redispatch fails to mitigate violations, Benders cuts are created and added to the master problem to revise the commitment solution. The iterative process between the commitment problem and the feasibility check subproblem will continue until simulated wind power scenarios can be accommodated by redispatch. Numerical simulations indicate the effectiveness of the proposed SCUC algorithm for managing the security of power system operation by taking into account the intermittency and volatility of wind power generation.

关键词： benders decomposition intermittency security-constrained unit commitment volatility wind power generation

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security-constrained unit commitment Considering Locational Frequency Stability in Low-Inertia Power Grids

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IEEE TRANSACTIONS ON POWER SYSTEMS 2023年第5期38卷 4134-4147页

作者： Tuo, Mingjian Li, Xingpeng Univ Houston Dept Elect & Comp Engn Houston TX 77204 USA

With increasing installation of wind and solar generation, conventional synchronous generators in power systems are gradually displaced resulting in a significant reduction in system inertia. Maintaining system frequency and rate-of-change-of-frequency (RoCoF) within acceptable ranges becomes more critical for the stability of a power system. This paper first discusses the impact of inter-area oscillations on the system rate-of-change-of-frequency (RoCoF) security;then, the limitations on locational RoCoF accounting for G - 1 contingency stability are derived. To capture highest locational RoCoF during the oscillation, multiple measurement windows are introduced. By enforcing these frequency related constraints, a location based RoCoF constrained security constrained unit commitment (LRC-SCUC) model is proposed. Furthermore, an effective piecewise linearization (PWL) technique is employed to formulate a RoCoF linearization problem and linearize the nonlinear function representing the location based RoCoF constraints in SCUC. Case studies are carried on IEEE 24-bus system to demonstrate the effectiveness of proposed LRC-SCUC model. The results also show that deploying virtual inertia techniques not only reduces the total cost, but also improves the system market efficiency.

关键词： Energy markets frequency stability inertia distribution linear programming low-inertia grid optimization security-constrained unit commitment virtual Inertia

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security-constrained unit commitment Considering Voltage Stability: A Parallel Solution 48

Security-Constrained Unit Commitment Considering Voltage Sta...

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48th North American Power Symposium (NAPS)

作者： Khanabadi, Mojtaba Wang, Chunheng Fu, Yong Mississippi State Univ Elect & Comp Engn Dept Mississippi State MS 39762 USA

ISBN: (纸本)9781509032709

security-constrained unit commitment (SCUC) is being executed every day to find the optimal hourly schedule over the next horizon of the time. In order to have a reliable and secure operation condition, it is desirable to include the AC networks constraints and the system's stability indices into the day-ahead generating scheduling problem of power systems. However, including such a non-convex set of constraints in the problem formulation, the complexity and size of the SCUC problem would increase;thus, the convexity of the mathematics model and the computational burden of the SCUC problem increases significantly. To avoid this issue, in this paper, we present a decentralized solution methodology where the voltage stability constrained SCUC (VSC-SCUC) problem is divided into multiple smaller subproblems;then, using the auxiliary problem principle (APP), the operating points of the subproblems are coordinated with each other iteratively in a parallel manner. In order to justify the effectiveness of the proposed method, several case studies are presented and discussed.

关键词： Decentralized optimization Lagrangian relaxation security-constrained unit commitment voltage stability

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